Method teaches generative AI models to locate personalized objects
After being trained with this technique, vision-language models can better identify a unique item in a new scene.
After being trained with this technique, vision-language models can better identify a unique item in a new scene.
A decade-plus alliance between MIT’s AgeLab and Toyota’s Collaborative Safety Research Center is recognized as a key contributor to advancements in automotive safety and human-machine interaction.
An algorithm can change the face of food assistance policy in the Global South, says MIT assistant professor and J-WAFS researcher Ali Aouad.
New tool from MIT CSAIL creates realistic virtual kitchens and living rooms where simulated robots can interact with models of real-world objects, scaling up training data for robot foundation models.
Analysis from MIT’s Center for Transportation and Logistics finds companies are still acting to reduce emissions, but often lag in measurement techniques.
By enabling users to easily create social apps that serve communities’ needs, the Graffiti framework aims to promote healthier online interactions.
Department of Mathematics researchers David Roe and Andrew Sutherland seek to advance automated theorem proving; four additional MIT alumni also awarded.
MIT-IBM Watson AI Lab researchers have developed a universal guide for estimating how large language models will perform based on smaller models in the same family.
J-PAL North America’s inaugural Climate Action Learning Lab provided six U.S. cities and states with customized training and resources to leverage data and evaluation to advance climate solutions that work.
Cache DNA has developed technologies that can preserve biomolecules at room temperature to make storing and transporting samples less expensive and more reliable.
Balancing automation and agency, Associate Professor Arvind Satyanarayan develops interactive data visualizations that amplify human creativity and cognition.
Artificially created data offer benefits from cost savings to privacy preservation, but their limitations require careful planning and evaluation, Kalyan Veeramachaneni says.
Professor Caroline Uhler discusses her work at the Schmidt Center, thorny problems in math, and the ongoing quest to understand some of the most complex interactions in biology.
VaxSeer uses machine learning to predict virus evolution and antigenicity, aiming to make vaccine selection more accurate and less reliant on guesswork.
The IECP will generate rigorous evidence for fair and effective public safety solutions.